Aim To develop a low-density polyethylene–hydroxyapatite (HA-PE) composite with properties tailored to function as a potential root canal filling material. Methodology Hydroxyapatite and polyethylene mixed with strontium oxide as a radiopacifier were extruded from a single screw extruder fitted with an appropriate die to form fibres. The composition of the composite was optimized with clinical handling and placement in the canal being the prime consideration. The fibres were characterized using infrared spectroscopy (FTIR), and their thermal properties determined using differential scanning calorimetry (DSC). The tensile strength and elastic modulus of the composite fibres and gutta-percha were compared, dry and after 1 month storage in simulated body fluid (SBF), using a universal testing machine. The radiopacity of the fibres was determined using digital radiography. The interaction of the composites with eugenol was evaluated and compared with gutta-percha. Data of the tensile test were submitted to two-way anova and Bonferroni tests (P < 0.05). Results The endothermic peaks obtained from the DSC studies showed that the melting point of the HA/PE composites ranged between 110.5 and 111.2 °C, whereas gutta-percha exhibited a melting point at 52 °C. The tensile strength and elastic modulus of the silanated HA/PE composites were significantly higher than those of gutta-percha (P < 0.0001) under dry conditions and 1 month storage in SBF. The gutta-percha in eugenol showed a significant increase in the polymer molar mass, whereas the silanated HA/PE composites were unchanged. Radiological evaluations demonstrated that silanated HA/PE fibres were sufficiently radiopaque. Conclusion Promising materials for endodontic applications have been developed, offering relevant benefits over the traditional materials in terms of mechanical and chemical properties
General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k
... Show MoreMoment invariants have wide applications in image recognition since they were proposed.
In the current study, haemoglobin analytes dissolved in a special buffer (KH2PO4(1M), K2HPO4(1M)) with pH of 7.4 were used to record absorption spectra measurements with a range of concentrations from (10-8 to 10-9) M and an absorption peak of 440nm using Broadband Cavity Enhanced Absorption Spectroscopy (BBCEAS) which is considered a simple, low cost, and robust setup. The principle work of this technique depends on the multiple reflections between the light source, which is represented by the Light Emitting Diode 3 W, and the detector, which is represented by the Avantes spectrophotomer. The optical cavity includes two high reflectivity ≥99% dielectric mirrors (dia
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